Rates of CTL killing in persistent viral infection in vivo

PCSK9 Manipulates Lipid Metabolism and the Immune Microenvironment in Cancer

Cancer remains the foremost cause of mortality on a global scale. Immunotherapy has yielded remarkable outcomes in the fight against cancer and is regarded as one of the most crucial and promising therapeutic modalities. PCSK9, a critical target for plasma lipids control, has been extensively and deeply studied in multiple diseases. Currently, the functions of PCSK9 in cancer, particularly its immunomodulatory role, have been progressively revealed. PCSK9 is capable of modulating a variety of immune response throughout tumor progression by orchestrating lipid metabolism. Moreover, PCSK9 governs the cell fate of diverse immune cells, such as inflammatory factor signals, MHC signals, and TCR signals. This review comprehensively summarizes the current state of knowledge regarding the role and underlying mechanisms of PCSK9 in tumorigenesis, progression, immune escape, and drug resistance.

PCSK9 in T-cell function and the immune response

Proprotein convertase subtilisin/kexin type 9 (PCSK9) was first reported in 2003 and confirmed to be strongly associated with familial hypercholesterolemia. Small-molecule inhibitors targeting PCSK9 provide an effective and safe method for managing hypercholesterolemia and reducing the cardiovascular risk. In recent years, increasing evidence has indicated other important roles for PCSK9 in inflammation, tumors, and even immune regulation. PCSK9 might be an attractive regulator of T-cell activation and expansion. It might mediate inflammation and regulate other types of immune cells. In this review, we summarize the current advances in the field of PCSK9 and provide a narrative of the biological processes associated with PCSK9. The relationships between PCSK9 and different T cells were investigated in depth. Finally, the signaling pathways associated with PCSK9 and the immune response are also summarized in this review.

Genetic Variability of Bovine Leukemia Virus: Evidence of Dual Infection, Recombination and Quasi-Species

We have characterized the intrahost genetic variation in the bovine leukemia virus (BLV) by examining 16 BLV isolates originating from the Western Siberia-Tyumen and South Ural-Chelyabinsk regions of Russia. Our research focused on determining the genetic composition of an 804 bp fragment of the BLV env gene, encoding for the entire gp51 protein. The results provide the first indication of the quasi-species genetic nature of BLV infection and its relevance for genome-level variation. Furthermore, this is the first phylogenetic evidence for the existence of a dual infection with BLV strains belonging to different genotypes within the same host: G4 and G7. We identified eight cases of recombination between these two BLV genotypes. The detection of quasi-species with cases of dual infection and recombination indicated a higher potential of BLV for genetic variability at the intra-host level than was previously considered.

Cytotoxic T-lymphocytes in acute myeloid leukemia: Monitoring prognosis and guiding treatment choice

BACKGROUND

Cytotoxic T-lymphocyte (CTL)-mediated therapy has become the central theme of cancer immunotherapy. The present study emphasized the role of CTLs in acute myeloid leukemia (AML) and aimed to understand the role of CTLs cytogenetic markers in monitoring AML prognostic outcomes and clinical treatment responses.

METHODS

Seurat was employed to analyze single-cell RNA sequencing data in GSE116256. CellChat was used to detect cell-cell interactions to determine the central role of CTLs. The marker genes of CTLs were extracted and randomForestSRC was employed to construct a random forest model. The prognosis, immune checkpoint expression, immune cell infiltration, immunotherapy response and drug sensitivity of AML patients were evaluated according to the model.

RESULTS

Seven types of cellular components of AML were identified in GSE116256, and CTLs radiated the most interactions with other cell types. Random forest analysis screened out six marker genes for construction of the model. The risk score calculated according to the model was positively correlated with immune score, immune cell infiltration, expression of multiple immune checkpoints and immune effect pathway. The response rate of immunotherapy was significantly higher and more sensitive to 14 drugs in high-risk samples than in low-risk samples, whereas low-risk patients showed a higher sensitivity to six drugs.

CONCLUSIONS

The present study emphasized the central role of CTLs in cell communication and established a random forest regression model based on its cytogenetic markers, which helps to stratify the prognosis of AML, promotes the understanding of the phenotype of AML and may also guide the treatment choice of AML patients, which contributed to stratification of AML prognosis, promoted understanding of the phenotype of AML and may guide treatment selection in patients with AML.

Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance ≅ 4-9mV 2 ) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

Cytotoxic T Lymphocytes Control Growth of B16 Tumor Cells in Collagen-Fibrin Gels by Cytolytic and Non-Lytic Mechanisms

Cytotoxic T lymphocytes (CTLs) are important in controlling some viral infections, and therapies involving the transfer of large numbers of cancer-specific CTLs have been successfully used to treat several types of cancers in humans. While the molecular mechanisms of how CTLs kill their targets are relatively well understood, we still lack a solid quantitative understanding of the kinetics and efficiency by which CTLs kill their targets in vivo. Collagen-fibrin-gel-based assays provide a tissue-like environment for the migration of CTLs, making them an attractive system to study T cell cytotoxicity in in vivo-like conditions. Budhu.et al. systematically varied the number of peptide (SIINFEKL)-pulsed B16 melanoma cells and SIINFEKL-specific CTLs (OT-1) and measured the remaining targets at different times after target and CTL co-inoculation into collagen-fibrin gels. The authors proposed that their data were consistent with a simple model in which tumors grow exponentially and are killed by CTLs at a per capita rate proportional to the CTL density in the gel. By fitting several alternative mathematical models to these data, we found that this simple "exponential-growth-mass-action-killing" model did not precisely describe the data. However, determining the best-fit model proved difficult because the best-performing model was dependent on the specific dataset chosen for the analysis. When considering all data that include biologically realistic CTL concentrations (E≤107cell/mL), the model in which tumors grow exponentially and CTLs suppress tumor's growth non-lytically and kill tumors according to the mass-action law (SiGMA model) fit the data with the best quality. A novel power analysis suggested that longer experiments (∼3-4 days) with four measurements of B16 tumor cell concentrations for a range of CTL concentrations would best allow discriminating between alternative models. Taken together, our results suggested that the interactions between tumors and CTLs in collagen-fibrin gels are more complex than a simple exponential-growth-mass-action killing model and provide support for the hypothesis that CTLs' impact on tumors may go beyond direct cytotoxicity.

Mathematical modeling suggests cytotoxic T lymphocytes control growth of B16 tumor cells in collagin-fibrin gels by cytolytic and non-lytic mechanisms

Cytotoxic T lymphocytes (CTLs) are important in controlling some viral infections, and therapies involving transfer of large numbers of cancer-specific CTLs have been successfully used to treat several types of cancers in humans. While molecular mechanisms of how CTLs kill their targets are relatively well understood we still lack solid quantitative understanding of the kinetics and efficiency at which CTLs kill their targets in different conditions. Collagen-fibrin gel-based assays provide a tissue-like environment for the migration of CTLs, making them an attractive system to study the cytotoxicity in vitro. Budhu et al. [1] systematically varied the number of peptide (SIINFEKL)- pulsed B16 melanoma cells and SIINFEKL-specific CTLs (OT-1) and measured remaining targets at different times after target and CTL co-inoculation into collagen-fibrin gels. The authors proposed that their data were consistent with a simple model in which tumors grow exponentially and are killed by CTLs at a per capita rate proportional to the CTL density in the gel. By fitting several alternative mathematical models to these data we found that this simple "exponential-growth-mass-action-killing" model does not precisely fit the data. However, determining the best fit model proved difficult because the best performing model was dependent on the specific dataset chosen for the analysis. When considering all data that include biologically realistic CTL concentrations ( E ≤ 10 ⁷ cell/ml) the model in which tumors grow exponentially and CTLs suppress tumor's growth non-lytically and kill tumors according to the mass-action law (SiGMA model) fitted the data with best quality. Results of power analysis suggested that longer experiments (∼ 3 - 4 days) with 4 measurements of B16 tumor cell concentrations for a range of CTL concentrations would best allow to discriminate between alternative models. Taken together, our results suggest that interactions between tumors and CTLs in collagen-fibrin gels are more complex than a simple exponential-growth- mass-action killing model and provide support for the hypothesis that CTLs impact on tumors may go beyond direct cytotoxicity.

The interactions between major immune effector cells and Hepatocellular Carcinoma: A systematic review

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common liver neoplasm with high morbidity and mortality. Tumor immunotherapy might be promising adjuvant therapy for HCC after surgery. To better develop HCC immunotherapy, comprehensive understanding of cell-cell interactions between immune effector cells and HCC cells remains crucial.

AIM

To review the existing studies to summarize the cell-cell interactions between major immune effector cells and HCC cells providing new data for HCC immunotherapy.

METHODS

A systematic review was conducted by searching PubMed database covering all papers published in recent five years up to January 2020. The guidelines of the preferred reporting items for systematic reviews were firmly followed.

RESULTS

There are 9 studies researching the interactions between CD8⁺ T lymphocytes and HCC cells and 22 studies researching that between natural killer (NK) cells and HCC cells. Among the 9 studies, 6 studies reported that CD8⁺ T lymphocytes showed cytotoxicity towards HCC cells while 3 studies found CD8⁺ T lymphocytes were impaired by HCC cells. Among the 22 studies, 20 studies presented that NK cells could inhibit HCC cells. Two studies were found to report NK cell dysfunction in HCC.

CONCLUSION

Based on the systematic analysis, we concluded that CD8⁺ T lymphocytes and NK cells can inhibit HCC cells. While in turn, HCC cells can also result in the dysfunction of those effector cells through various mechanisms. Organoids and direct contact cell co-culture with primary HCC cells and TILs should be the most innovative way to investigate the interactions and develop novel immunotherapy.

Evaluation of CD8 T cell killing models with computer simulations of 2-photon imaging experiments

In vivo imaging of cytotoxic T lymphocyte (CTL) killing activity revealed that infected cells have a higher observed probability of dying after multiple contacts with CTLs. We developed a three-dimensional agent-based model to discriminate different hypotheses about how infected cells get killed based on quantitative 2-photon in vivo observations. We compared a constant CTL killing probability with mechanisms of signal integration in CTL or infected cells. The most likely scenario implied increased susceptibility of infected cells with increasing number of CTL contacts where the total number of contacts was a critical factor. However, when allowing in silico T cells to initiate new interactions with apoptotic target cells (zombie contacts), a contact history independent killing mechanism was also in agreement with experimental datasets. The comparison of observed datasets to simulation results, revealed limitations in interpreting 2-photon data, and provided readouts to distinguish CTL killing models.

A biological profile for diagnosis and outcome of COVID-19 patients

Objectives As severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) pandemic is increasing its victims on a global scale with recurring outbreaks, it remains of outmost importance to rapidly identify people requiring an intensive care unit (ICU) hospitalization. The aim of this study was to identify Coronavirus Disease 2019 (COVID-19) biomarkers, to investigate their correlation with disease severity and to evaluate their usefulness for follow-up. Methods Fifty patients diagnosed with SARS-Cov-2 were included in March 2020. Clinical and biological data were collected at admission, during hospitalization and one month after discharge. Patients were divided into two severity groups: non-ICU (28) and ICU and/or death (22) to stratify the risk. Results Blood parameters in COVID-19 patients at admission showed increased C-reactive protein (CRP) (100%), ferritin (92%), lactate dehydrogenase (LDH) (80%), white blood cell (WBC) count (26%) with lymphopenia (52%) and eosinopenia (98%). There were significant differences in levels of CRP, ferritin, D-dimers, fibrinogen, lymphocyte count, neutrophil count and neutrophil-to-lymphocyte ratio (NLR) among the two severity groups. Mapping of biomarker's kinetics distinguished early and late parameters. CRP, ferritin, LDH, lymphopenia and eosinopenia were present upon admission with a peak at the first week. Late biomarkers such as anemia, neutrophilia and elevated liver biomarkers appeared after one week with a peak at three weeks of hospitalization. Conclusions We confirmed that high-values of CRP, NLR, D-dimers, ferritin as well as lymphopenia and eosinopenia were consistently found and are good markers for risk stratification. Kinetics of these biomarkers correlate well with COVID-19 severity. Close monitoring of early and late biomarkers is crucial in the management of critical patients to avoid preventable deaths.

Heterogeneous, delayed-onset killing by multiple-hitting T cells: Stochastic simulations to assess methods for analysis of imaging data

Although quantitative insights into the killing behaviour of Cytotoxic T Lymphocytes (CTLs) are necessary for the rational design of immune-based therapies, CTL killing function remains insufficiently characterised. One established model of CTL killing treats CTL cytotoxicity as a Poisson process, based on the assumption that CTLs serially kill antigen-presenting target cells via delivery of lethal hits, each lethal hit corresponding to a single injection of cytotoxic proteins into the target cell cytoplasm. Contradicting this model, a recent in vitro study of individual CTLs killing targets over a 12-hour period found significantly greater heterogeneity in CTL killing performance than predicted by Poisson-based killing. The observed killing process was dynamic and varied between CTLs, with the best performing CTLs exhibiting a marked increase in killing during the final hours of the experiments, along with a "burst killing" kinetic. Despite a search for potential differences between CTLs, no mechanistic explanation for the heterogeneous killing kinetics was found. Here we have used stochastic simulations to assess whether target cells might require multiple hits from CTLs before undergoing apoptosis, in order to verify whether multiple-hitting could explain the late onset, burst killing dynamics observed in vitro. We found that multiple-hitting from CTLs was entirely consistent with the observed killing kinetics. Moreover, the number of available targets and the spatiotemporal kinetics of CTL:target interactions influenced the realised CTL killing rate. We subsequently used realistic, spatial simulations to assess methods for estimating the hitting rate and the number of hits required for target death, to be applied to microscopy data of individual CTLs killing targets. We found that measuring the cumulative duration of individual contacts that targets have with CTLs would substantially improve accuracy when estimating the killing kinetics of CTLs.

Cancer-induced immunosuppression can enable effectiveness of immunotherapy through bistability generation: A mathematical and computational examination

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The presence of an immunological barrier in cancer- immune system interaction (CISI) is consistent with the bistability patterns in that system.

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In CISI models, bistability patterns are consistent with immunosuppressive effects dominating immunoproliferative effects.

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Bistability could be harnessed to devise effective combination immunotherapy approaches.

Cancer immunotherapies rely on how interactions between cancer and immune system cells are constituted. The more essential to the emergence of the dynamical behavior of cancer growth these interactions are, the more effectively they may be used as mechanisms for interventions. Mathematical modeling can help unearth such connections, and help explain how they shape the dynamics of cancer growth. Here, we explored whether there exist simple, consistent properties of cancer-immune system interaction (CISI) models that might be harnessed to devise effective immunotherapy approaches. We did this for a family of three related models of increasing complexity. To this end, we developed a base model of CISI, which captures some essential features of the more complex models built on it. We find that the base model and its derivates can plausibly reproduce biological behavior that is consistent with the notion of an immunological barrier. This behavior is also in accord with situations in which the suppressive effects exerted by cancer cells on immune cells dominate their proliferative effects. Under these circumstances, the model family may display a pattern of bistability, where two distinct, stable states (a cancer-free, and a full-grown cancer state) are possible. Increasing the effectiveness of immune-caused cancer cell killing may remove the basis for bistability, and abruptly tip the dynamics of the system into a cancer-free state. Additionally, in combination with the administration of immune effector cells, modifications in cancer cell killing may be harnessed for immunotherapy without the need for resolving the bistability. We use these ideas to test immunotherapeutic interventions in silico in a stochastic version of the base model. This bistability-reliant approach to cancer interventions might offer advantages over those that comprise gradual declines in cancer cell numbers.

Designing of CD8+ and CD8+-overlapped CD4+ epitope vaccine by targeting late and early proteins of human papillomavirus

BACKGROUND AND AIM

Human papillomavirus (HPV) is an oncogenic agent that causes over 90% of cases of cervical cancer in the world. Currently available prophylactic vaccines are type specific and have less therapeutic efficiency. Therefore, we aimed to predict the potential species-specific and therapeutic epitopes from the protein sequences of HPV45 by using different immunoinformatics tools.

METHODS

Initially, we determined the antigenic potential of late (L1 and L2) and early (E1, E2, E4, E5, E6, and E7) proteins. Then, major histocompatibility complex class I-restricted CD8+ T-cell epitopes were selected based on their immunogenicity. In addition, epitope conservancy, population coverage (PC), and target receptor-binding affinity of the immunogenic epitopes were determined. Moreover, we predicted the possible CD8+, nested interferon gamma (IFN-γ)-producing CD4+, and linear B-cell epitopes. Further, antigenicity, allergenicity, immunogenicity, and system biology-based virtual pathway associated with cervical cancer were predicted to confirm the therapeutic efficiency of overlapped epitopes.

RESULTS

Twenty-seven immunogenic epitopes were found to exhibit cross-protection (≥55%) against the 15 high-risk HPV strains (16, 18, 31, 33, 35, 39, 51, 52, 56, 58, 59, 68, 69, 73, and 82). The highest PC was observed in Europe (96.30%), North America (93.98%), West Indies (90.34%), North Africa (90.14%), and East Asia (89.47%). Binding affinities of 79 docked complexes observed as global energy ranged from -10.80 to -86.71 kcal/mol. In addition, CD8+ epitope-overlapped segments in CD4+ and B-cell epitopes demonstrated that immunogenicity and IFN-γ-producing efficiency ranged from 0.0483 to 0.5941 and 0.046 to 18, respectively. Further, time core simulation revealed the overlapped epitopes involved in pRb, p53, COX-2, NF-X1, and HPV45 infection signaling pathways.

CONCLUSION

Even though the results of this study need to be confirmed by further experimental peptide sensitization studies, the findings on immunogenic and IFN-γ-producing CD8+ and overlapped epitopes provide new insights into HPV vaccine development.

Immunocompetence and mechanism of the DRibble-DCs vaccine for oral squamous cell carcinoma

Background

Due to the high-quality immunogenicity of tumor-derived autophagosomes (DRibbles), we aimed to explore the antitumor ability and mechanism of DRibble-loaded dendritic cells (DRibble-DCs).

Materials and methods

DRibbles extracted from the oral squamous cell carcinoma cell line SCC7 express specific LC3-II and ubiquitination marker. Immunization of mice with the DRibble-DCs vaccine led to the proliferation and differentiation of CD3⁺CD4⁺IFN-γ⁺ and CD3⁺CD8⁺IFN-γ⁺ T cells. The expression of proteins in endoplasmic reticulum stress (ERS) pathways was determined by Western blotting. Additionally, the functional properties of the DRibble-DCs were examined in mice, and regulatory T cells were measured by flow cytometry.

Results

Excellent biocompatibility was observed in vitro when DCs were loaded with DRibbles. T cells of lymph nodes and spleens from mice immunized with DRibble-DCs had cytotoxic effects on SCC7 cells. DCs homeostasis and ERS-related proteins were affected by DRibbles. Moreover, the DRibble-DCs vaccine achieved significantly better antitumor efficacy than DRibbles and tumor cell lysate-loaded DCs.

Conclusion

The results validated the antitumor immune responses to the DRibble-DCs vaccine in vivo and in vitro. The ERS pathway can be affected by DRibbles.

Derivative-Free Optimization of Rate Parameters of Capsid Assembly Models from Bulk in Vitro Data

The assembly of virus capsids proceeds by a complicated cascade of association and dissociation steps, the great majority of which cannot be directly experimentally observed. This has made capsid assembly a rich field for computational models, but there are substantial obstacles to model inference for such systems. Here, we describe progress on fitting kinetic rate constants defining capsid assembly models to experimental data, a difficult data-fitting problem because of the high computational cost of simulating assembly trajectories, the stochastic noise inherent to the models, and the limited and noisy data available for fitting. We evaluate the merits of data-fitting methods based on derivative-free optimization (DFO) relative to gradient-based methods used in prior work. We further explore the advantages of alternative data sources through simulation of a model of time-resolved mass spectrometry data, a technology for monitoring bulk capsid assembly that can be expected to provide much richer data than previously used static light scattering approaches. The results show that advances in both the data and the algorithms can improve model inference. More informative data sources lead to high-quality fits for all methods, but DFO methods show substantial advantages on less informative data sources that better represent current experimental practice.

Within-Epitope Interactions Can Bias CTL Escape Estimation in Early HIV Infection

As human immunodeficiency virus (HIV) begins to replicate within hosts, immune responses are elicited against it. Escape mutations in viral epitopes—immunogenic peptide parts presented on the surface of infected cells—allow HIV to partially evade these responses, and thus rapidly go to fixation. The faster they go to fixation, i.e., the higher their escape rate, the larger the selective pressure exerted by the immune system is assumed to be. This relation underpins the rationale for using escapes to assess the strength of immune responses. However, escape rate estimates are often obtained by employing an aggregation procedure, where several mutations that affect the same epitope are aggregated into a single, composite epitope mutation. The aggregation procedure thus rests upon the assumption that all within-epitope mutations have indistinguishable effects on immune recognition. In this study, we investigate how violation of this assumption affects escape rate estimates. To this end, we extend a previously developed simulation model of HIV that accounts for mutation, selection, and recombination to include different distributions of fitness effects (DFEs) and inter-mutational genomic distances. We use this discrete time Wright–Fisher based model to simulate early within-host evolution of HIV for DFEs and apply standard estimation methods to infer the escape rates. We then compare true with estimated escape rate values. We also compare escape rate values obtained by applying the aggregation procedure with values estimated without use of that procedure. We find that across the DFEs analyzed, the aggregation procedure alters the detectability of escape mutations: large-effect mutations are overrepresented while small-effect mutations are concealed. The effect of the aggregation procedure is similar to extracting the largest-effect mutation appearing within an epitope. Furthermore, the more pronounced the over-exponential decay of the DFEs, the more severely true escape rates are underestimated. We conclude that the aggregation procedure has two main consequences. On the one hand, it leads to a misrepresentation of the DFE of fixed mutations. On the other hand, it conceals within-epitope interactions that may generate irregularities in mutation frequency trajectories that are thus left unexplained.

Granulocyte-macrophage colony-stimulating factor, a potent adjuvant for polarization to Th-17 pattern: an experience on HIV-1 vaccine model

Cytokines are mediators for polarization of immune response in vaccines. Studies show that co-immunization of DNA vaccines with granulocyte-macrophage colony-stimulating factor (GM-CSF) can increase immune responses. Here, experimental mice were immunized with HIV-1_{tat/pol/gag/env} DNA vaccine with GM-CSF and boosted with recombinant vaccine. Lymphocyte proliferation with Brdu and CTL activity, IL-4, IFN-γ, IL-17 cytokines, total antibody, and IgG1 and IgG2a isotypes were assessed with ELISA. Results show that GM-CSF as adjuvant in DNA immunization significantly increased lymphocyte proliferation and IFN-γ cytokines, but CTL response was tiny increased. Also GM-CSF as adjuvant decreased IL-4 cytokine vs mere vaccine group. IL-17 in the group that immunized with mixture of DNA vaccine/GM-CSF was significantly increased vs DNA vaccine group. Result of total antibody shows that GM-CSF increased antibody response in which both IgG1 and IgG2a increased. Overall, results confirmed the beneficial effect of GM-CSF as adjuvant to increase vaccine immunogenicity. The hallmark result of this study was to increase IL-17 cytokine with DNA vaccine/GM-CSF immunized group. This study for the first time provides the evidence of the potency of GM-CSF in the induction of IL-17 in response to a vaccine, which is important for control of infection such as HIV-1.

Mechanisms and Dynamics of T Cell-Mediated Cytotoxicity In Vivo

Cytotoxic T lymphocytes (CTLs) are critical in the elimination of infected or malignant cells and are emerging as a major therapeutic target. How CTLs recognize and kill harmful cells has been characterized in vitro but little is known about these processes in the living organism. Here we review recent insights into CTL-mediated killing with an emphasis on in vivo CTL biology. Specifically, we focus on the possible rate-limiting steps determining the efficiency of CTL-mediated killing. We also highlight the need for cell-based datasets that permit the quantification of CTL dynamics, including CTL location, migration, and killing rates. A better understanding of these factors is required to predict protective CD8 T cell immunity in vivo and to design optimized vaccination protocols.

Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics

The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical, and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body’s viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation.

A novel metapopulation model of HIV suggests that within-host infections are characterized by a highly dynamic process of localized infection followed by clearance within T cell centers.

When a person is infected with HIV, the initial peak level of virus in the blood is usually very high before a lower, relatively stable level is reached and maintained for the duration of the chronic infection. This stable level is known as the set-point viral load (SPVL) and is associated with severity of infection. SPVL is also highly variable among patients, ranging from 100 to a million copies of the virus per mL of blood. The replicative capacity of the infecting virus and the strength of the immune response both influence SPVL. However, standard mathematical models show that variation in these two factors cannot easily reproduce the observed distribution of SPVL among patients. Standard models typically treat infected individuals as well-mixed systems, but in reality viral replication is localised in T-cell centres, or patches, found in secondary lymphoid tissue. To account for this population structure, we developed a carefully parameterised metapopulation model. We find the system can reach a steady state at which the viral load in the blood is relatively stable, representing SPVL, but surprisingly, the patches are highly dynamic, characterised by bursts of infection followed by elimination of virus due to localised host immune responses. Significantly, this model can reproduce the wide distribution of SPVLs found among infected individuals for realistic distributions of viral replicative capacity and strength of immune response. Our model can also be used in the future to understand other aspects of chronic HIV infection.

Notwithstanding Circumstantial Alibis, Cytotoxic T Cells Can Be Major Killers of HIV-1-Infected Cells

Several experiments suggest that in the chronic phase of human immunodeficiency virus type 1 (HIV-1) infection, CD8⁺ cytotoxic T lymphocytes (CTL) contribute very little to the death of productively infected cells. First, the expected life span of productively infected cells is fairly long, i.e., about 1 day. Second, this life span is hardly affected by the depletion of CD8⁺ T cells. Third, the rate at which mutants escaping a CTL response take over the viral population tends to be slow. Our main result is that all these observations are perfectly compatible with killing rates that are much faster than one per day once we invoke the fact that infected cells proceed through an eclipse phase of about 1 day before they start producing virus. Assuming that the major protective effect of CTL is cytolytic, we demonstrate that mathematical models with an eclipse phase account for the data when the killing is fast and when it varies over the life cycle of infected cells. Considering the steady state corresponding to the chronic phase of the infection, we find that the rate of immune escape and the rate at which the viral load increases following CD8⁺ T cell depletion should reflect the viral replication rate, ρ. A meta-analysis of previous data shows that viral replication rates during chronic infection vary between 0.5 ≤ ρ ≤ 1 day⁻¹. Balancing such fast viral replication requires killing rates that are several times larger than ρ, implying that most productively infected cells would die by cytolytic effects.

IMPORTANCE Most current data suggest that cytotoxic T cells (CTL) mediate their control of human immunodeficiency virus type 1 (HIV-1) infection by nonlytic mechanisms; i.e., the data suggest that CTL hardly kill. This interpretation of these data has been based upon the general mathematical model for HIV infection. Because this model ignores the eclipse phase between the infection of a target cell and the start of viral production by that cell, we reanalyze the same data sets with novel models that do account for the eclipse phase. We find that the data are perfectly consistent with lytic control by CTL and predict that most productively infected cells are killed by CTL. Because the killing rate should balance the viral replication rate, we estimate both parameters from a large set of published experiments in which CD8⁺ T cells were depleted in simian immunodeficiency virus (SIV)-infected monkeys. This confirms that the killing rate can be much faster than is currently appreciated.

Models of Viral Population Dynamics

Models of viral population dynamics have contributed enormously to our understanding of the pathogenesis and transmission of several infectious diseases, the coevolutionary dynamics of viruses and their hosts, the mechanisms of action of drugs, and the effectiveness of interventions. In this chapter, we review major advances in the modeling of the population dynamics of the human immunodeficiency virus (HIV) and briefly discuss adaptations to other viruses.

In Vivo Killing Capacity of Cytotoxic T Cells Is Limited and Involves Dynamic Interactions and T Cell Cooperativity

According to in vitro assays, T cells are thought to kill rapidly and efficiently, but the efficacy and dynamics of cytotoxic T lymphocyte (CTL)-mediated killing of virus-infected cells in vivo remains elusive. We used two-photon microscopy to quantify CTL-mediated killing in mice infected with herpesviruses or poxviruses. On average, one CTL killed 2–16 virus-infected cells per day as determined by real-time imaging and by mathematical modeling. In contrast, upon virus-induced MHC class I downmodulation, CTLs failed to destroy their targets. During killing, CTLs remained migratory and formed motile kinapses rather than static synapses with targets. Viruses encoding the calcium sensor GCaMP6s revealed strong heterogeneity in individual CTL functional capacity. Furthermore, the probability of death of infected cells increased for those contacted by more than two CTLs, indicative of CTL cooperation. Thus, direct visualization of CTLs during killing of virus-infected cells reveals crucial parameters of CD8⁺ T cell immunity.

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Two-photon imaging indicates that CTLs kill 2–16 virus-infected cells per day

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CTLs form kinapses rather than stable synapses when killing virus-infected cells

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Some CTL contacts trigger long-lasting calcium fluxes in virus-infected cells

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CTLs can cooperate during killing of virus-infected cells

Novel CD8(+) cytotoxic T cell epitopes in bovine leukemia virus with cattle

Bovine leukemia virus (BLV) is associated with enzootic bovine leukosis and is closely related to human T cell leukemia virus (HTLV). The cytotoxic T lymphocyte (CTL) plays a key role in suppressing the progression of disease caused by BLV. T and B cell epitopes in BLV have been studied, but CD8(+) CTL epitopes remain poorly understood. We used a library of 115 synthetic peptides covering the entirety of the Env proteins (gp51 and gp30), the Gag proteins (p15, p24, and p12), and the Tax protein of BLV to identify 11 novel CD8(+) T cell epitopes (gp51N5, gp51N11, gp51N12, gp30N5, gp30N6, gp30N8, gp30N16, tax16, tax18, tax19, and tax20) in four calves experimentally infected with BLV. The number of CD8(+) T cell epitopes that could be identified in each calf correlated with the BLV proviral load. Interestingly, among the 11 epitopes identified, only gp51N11 was capable of inducing CD8(+) T cell-mediated cytotoxicity in all four calves, but it is not a suitable vaccine target because it shows a high degree of polymorphism according to the Wu-Kabat variability index. By contrast, no CTL epitopes were identified from the Gag structural protein. In addition, several epitopes were obtained from gp30 and Tax, indicating that cellular immunity against BLV is strongly targeted to these proteins. CD8(+) CTL epitopes from gp30 and Tax were less polymorphic than epitopes from. Indeed, peptides tax16, tax18, tax19, and tax20 include a leucine-rich activation domain that encompasses a transcriptional activation domain, and the gp30N16 peptide contains a proline-rich region that interacts with a protein tyrosine phosphatase SHP1 to regulate B cell activation. Moreover, at least one CD8(+) CTL epitope derived from gp30 was identified in each of the four calves. These results indicate that BLV gp30 may be the best candidate for the development of a BLV vaccine.

What do mathematical models tell us about killing rates during HIV-1 infection?

Over the past few decades the extent to which cytotoxic T lymphocytes (CTLs) control human immunodeficiency virus (HIV) replication has been studied extensively, yet their role and mode of action remain controversial. In some studies, CTLs were found to kill a large fraction of the productively infected cells relative to the viral cytopathicity, whereas in others CTLs were suggested to kill only a small fraction of infected cells. In this review, we compile published estimates of CTL-mediated death rates, and examine whether these studies permit determining the rate at which CTLs kill HIV-1 infected cells. We highlight potential misinterpretations of the CTL-killing rates from the escape rates of mutants, and from perturbations of the steady state viral load during chronic infection. Our major conclusion is that CTL-mediated killing rates remain unknown. But contrary to current consensus, we argue that killing rates higher than one per day are perfectly consistent with the experimental data, which would imply that the majority of the productively infected cells could still die from CTL-mediated killing rather than from viral cytopathicity.

Estimating the In Vivo Killing Efficacy of Cytotoxic T Lymphocytes across Different Peptide-MHC Complex Densities

Cytotoxic T lymphocytes (CTLs) are important agents in the control of intracellular pathogens, which specifically recognize and kill infected cells. Recently developed experimental methods allow the estimation of the CTL's efficacy in detecting and clearing infected host cells. One method, the in vivo killing assay, utilizes the adoptive transfer of antigen displaying target cells into the bloodstream of mice. Surprisingly, killing efficacies measured by this method are often much higher than estimates obtained by other methods based on, for instance, the dynamics of escape mutations. In this study, we investigated what fraction of this variation can be explained by differences in peptide loads employed in in vivo killing assays. We addressed this question in mice immunized with lymphocytic choriomeningitis virus (LCMV). We conducted in vivo killing assays varying the loads of the immunodominant epitope GP33 on target cells. Using a mathematical model, we determined the efficacy of effector and memory CTL, as well as CTL in chronically infected mice. We found that the killing efficacy is substantially reduced at lower peptide loads. For physiological peptide loads, our analysis predicts more than a factor 10 lower CTL efficacies than at maximum peptide loads. Assuming that the efficacy scales linearly with the frequency of CTL, a clear hierarchy emerges among the groups across all peptide antigen concentrations. The group of mice with chronic LCMV infections shows a consistently higher killing efficacy per CTL than the acutely infected mouse group, which in turn has a consistently larger efficacy than the memory mouse group. We conclude that CTL killing efficacy dependence on surface epitope frequencies can only partially explain the variation in in vivo killing efficacy estimates across experimental methods and viral systems, which vary about four orders of magnitude. In contrast, peptide load differences can explain at most two orders of magnitude.

Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection

HIV-1 can disseminate between susceptible cells by two mechanisms: cell-free infection following fluid-phase diffusion of virions and by highly-efficient direct cell-to-cell transmission at immune cell contacts. The contribution of this hybrid spreading mechanism, which is also a characteristic of some important computer worm outbreaks, to HIV-1 progression in vivo remains unknown. Here we present a new mathematical model that explicitly incorporates the ability of HIV-1 to use hybrid spreading mechanisms and evaluate the consequences for HIV-1 pathogenenesis. The model captures the major phases of the HIV-1 infection course of a cohort of treatment naive patients and also accurately predicts the results of the Short Pulse Anti-Retroviral Therapy at Seroconversion (SPARTAC) trial. Using this model we find that hybrid spreading is critical to seed and establish infection, and that cell-to-cell spread and increased CD4+ T cell activation are important for HIV-1 progression. Notably, the model predicts that cell-to-cell spread becomes increasingly effective as infection progresses and thus may present a considerable treatment barrier. Deriving predictions of various treatments' influence on HIV-1 progression highlights the importance of earlier intervention and suggests that treatments effectively targeting cell-to-cell HIV-1 spread can delay progression to AIDS. This study suggests that hybrid spreading is a fundamental feature of HIV infection, and provides the mathematical framework incorporating this feature with which to evaluate future therapeutic strategies.

The route of HIV escape from immune response targeting multiple sites is determined by the cost-benefit tradeoff of escape mutations

Cytotoxic T lymphocytes (CTL) are a major factor in the control of HIV replication. CTL arise in acute infection, causing escape mutations to spread rapidly through the population of infected cells. As a result, the virus develops partial resistance to the immune response. The factors controlling the order of mutating epitope sites are currently unknown and would provide a valuable tool for predicting conserved epitopes. In this work, we adapt a well-established mathematical model of HIV evolution under dynamical selection pressure from multiple CTL clones to include partial impairment of CTL recognition, , as well as cost to viral replication, . The process of escape is described in terms of the cost-benefit tradeoff of escape mutations and predicts a trajectory in the cost-benefit plane connecting sequentially escaped sites, which moves from high recognition loss/low fitness cost to low recognition loss/high fitness cost and has a larger slope for early escapes than for late escapes. The slope of the trajectory offers an interpretation of positive correlation between fitness costs and HLA binding impairment to HLA-A molecules and a protective subset of HLA-B molecules that was observed for clinically relevant escape mutations in the Pol gene. We estimate the value of from published experimental studies to be in the range (0.01–0.86) and show that the assumption of complete recognition loss () leads to an overestimate of mutation cost. Our analysis offers a consistent interpretation of the commonly observed pattern of escape, in which several escape mutations are observed transiently in an epitope. This non-nested pattern is a combined effect of temporal changes in selection pressure and partial recognition loss. We conclude that partial recognition loss is as important as fitness loss for predicting the order of escapes and, ultimately, for predicting conserved epitopes that can be targeted by vaccines.

Like many viruses, HIV has evolved mechanisms to evade the host immune response. As early as a few weeks after infection is initiated, mutations appear in the viral genome that reduce the ability of cytotoxic T lymphocytes (CTL) to control virus replication. However, of the many mutations in the viral genome that could potentially mediate viral escape from the CTL response, a specific subset are typically observed. This suggests that some mutations either entail too high a fitness cost for the virus, or are relatively inefficient escape mutations. A successful vaccine would target the CTL response to these regions in such a way that escape would not be possible. We use a computational model of HIV infection in order to study the factors that determine whether a given escape mutation will occur, how long it will be maintained in the population, and how these changes in the viral genome will affect the CTL response. Our analysis highlights the important role of partial recognition loss conferred by a mutation in producing the complex dynamics of escape that are observed during the course of infection.

Vaccination against δ-retroviruses: the bovine leukemia virus paradigm

Bovine leukemia virus (BLV) and human T-lymphotropic virus type 1 (HTLV-1) are closely related δ-retroviruses that induce hematological diseases. HTLV-1 infects about 15 million people worldwide, mainly in subtropical areas. HTLV-1 induces a wide spectrum of diseases (e.g., HTLV-associated myelopathy/tropical spastic paraparesis) and leukemia/lymphoma (adult T-cell leukemia). Bovine leukemia virus is a major pathogen of cattle, causing important economic losses due to a reduction in production, export limitations and lymphoma-associated death. In the absence of satisfactory treatment for these diseases and besides the prevention of transmission, the best option to reduce the prevalence of δ-retroviruses is vaccination. Here, we provide an overview of the different vaccination strategies in the BLV model and outline key parameters required for vaccine efficacy.